Study of Fuzzy Neural Network on Wind Velocity Control of Low-Speed Wind Tunnel

In this paper, a wind velocity control system of low-speed wind tunnel has been built in Inner Mongolia Agricultural University. Due to the difficulties of establishing mathematical model, the complicated nonlinear characteristics and the change of parameters, the wind velocity system is not easy to control in classical PID algorithm. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. Simulation results illustrate the effectiveness of the designed wind velocity control system for low-speed wind tunnel.